Hello everyone in biostars. I'm trying to do a go, kegg analysis. But I'm having an error. I'm using the following code. reference from github
library(AnnotationHub)
ah <- AnnotationHub()
query(ah,'Oryza_sativa')
rice <- ah[['AH107684']]
rice
library(clusterProfiler)
setwd("C:/Users/R")
deseqas <- read.csv('deg.csv')
as <- deseqas$gene
geneList = sort(as, decreasing = TRUE)
IDtable <- read.csv("go/riceIDtable.csv")
genes_eid <- IDtable[match(geneList, IDtable$rapdb), "entrezgene"]
genes_eid <- as.character(genes_eid[!is.na(genes_eid)])
genes_eid = sort(genes_eid, decreasing = TRUE)
ego3 <- gseGO(geneList = genes_eid, OrgDb = rice, ont = "BP", minGSSize = 100, maxGSSize = 500, pvalueCutoff = 0.05, verbose = FALSE)
and result is --> Expected input gene ID: 4351482,9271816,4347514,4351482,4341462,4348447 Error in check_gene_id(geneList, geneSets) : --> No gene can be mapped....
so i want to know how to solve this problem. plz....
1 answer
The error is self explanatory, the gene list you have provided the gseGO function with is not in the expected format. Since we don't have access to your actual gene list it's hard to help but you can use the keyType argument inside the function to tell the function what gene format to expect, for example "keyType = "ENTREZID"". See here from the package vignette for more.
I used keyType = “ENTREZID” as an example here, ONLY if the gene list provided is standard entrez id you could readily use it otherwise you have to convert your gene list to entrez id or use other gene name system recognizable by the function. That’s what the error meant. It says the function expects gene names in formats like 4351482, 9271816, 4347514, etc but what you have currently provided does not match this so no gene could be mapped.
We don’t have access to your gene list since you have not provided a reproducible example, but you can print your genes_eid object to see what is the gene names format of your DEG list.
thanks for your reply sincerely When I matched input data with key type, I got output. However, the results were as follows.
...pvalues adjusted by 'BH' with cutoff <0.05
...0 enriched terms found
...Citation
To verify this, I used [shinygo 0.77] (http://bioinformatics.sdstate.edu/go/) and get some go enrichment results. Is there any way to solve this problem??.
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